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Research on Maximizing Influence of Blockchain Social Network Based on BCLT Model

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  • Chang Liu
  • Sheng Bin
  • Giulio E. Cantarella

Abstract

In the blockchain social network, the traditional influence maximization algorithm has the problem of insufficient accuracy of the influence spread. To solve the above problem, a BCLT model including the characteristics of the blockchain is established based on the linear threshold model. The BC-RIS algorithm is proposed based on the reverse reachable set. The BC-RIS algorithm's influence spread and running time and the traditional algorithm is compared using the real blockchain social network data set. The experimental results show that the BC-RIS algorithm can obtain a larger influence spread range, which is more in line with the influence propagation law of the blockchain social network.

Suggested Citation

  • Chang Liu & Sheng Bin & Giulio E. Cantarella, 2022. "Research on Maximizing Influence of Blockchain Social Network Based on BCLT Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-8, May.
    • Handle: RePEc:hin:jnddns:7335390
    DOI: 10.1155/2022/7335390
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